The ESKAPE pathogens continue to pose a significant global health risk due to the prevalence of multidrug resistance and widespread rates of infection. New therapies are thus highly desired, and we propose leveraging combinations of antibiotics to both improve efficacy and manage drug resistance. Optimal multi-drug regimens consider how each drug affects the efficacy of others. Synergistic multi-drug treatments against the ESKAPE pathogens may transform patient care by providing more potent synergistic therapies, allowing dosing at levels that lower the rate of drug-dependent morbidity, and quickly shrinking pathogen populations, possibly slowing drug resistance acquisition. We have developed experimental and analytical platforms to efficiently measure, analyze, and predict pairwise and high-order drug interactions, allowing us to prioritize combinations from a large numbers of drugs. We propose to build upon our platforms to accelerate the development of combination therapies against three important nosocomial ESKAPE pathogens: Acinetobacter baumannii (Ab), Klebsiella pneumonia (Kp), and Pseudomonas aeruginosa (Pa). Treatment of these ESKAPE pathogens is currently limited because of their remarkable ability to acquire drug resistance and escape treatment. Promising combination therapies against ESKAPE pathogens are being developed ad hoc today, illustrating the need for systematic strategies that employ this approach. To fully realize the potential of new drug candidates and optimize their use against ESKAPE pathogens, we propose to systematically explore combination therapy early in the development pipeline. We will leverage the scale and efficiency of a well-validated micro-scale screening approach to measure the efficacies and interactions of pairwise combinations among 25 antibiotics and small molecule libraries and new chemical entities including biologics and conjugates discovered in projects 1, 3, and 4. Discovery will consist of screening against resistant clinical isolates. We will rigorously validate screening hits and prioritize these by chemical progressibility, evaluation of market need, and in tests against clinical isolate panels, expanded antibiotic sets, basic toxicity assessment, and efficacy in more complex growth-niche conditions (such as host-like environmental conditions, biofilms, and in animal models). Combinations that display favorable characteristics in preliminary analyses will be subjected to further intensive mechanism-of-action and resistance acquisition studies. Based on these data, we will predict interactions with further available compounds in our hit set and test engineered higher-order combination therapies. Priority leads will be systematically optimized in a substantial medicinal chemistry effort aimed at engineering a comprehensive product characteristic profile and extending through in vivo proof of concept (PoC). We anticipate that this work will identify potent candidate drug regimens that are commercially attractive and have a strong scientific basis for translation to the clinic.